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Machine Learning Engineer Quantization Jobs in Lincoln, CA

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

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AI Solutions Architect

Sacramento, CA

$67.25 - $88.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

AI Data Engineer - Manager

Sacramento, CA

$122K - $146K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

Generative AI Engineer III

Sacramento, CA

$61.25 - $82.25/hr

Design, build, test, and deploy machine learning and artificial intelligence solutions for business ... Collaborate with engineers, data scientists, product stakeholders, and business teams to translate ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Agentic DevOps Engineer

Sacramento, CA · On-site

$70K - $205K/yr

You Are As an Artificial Intelligence and Machine Learning Computational Science professional, you ... Engineer to support our Agentic DevOps initiatives. This role is ideal for a hands-on technical ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Machine Learning Engineer Quantization information

See Lincoln, CA salary details

$32.9K

$134.4K

$202K

How much do machine learning engineer quantization jobs pay per year?

As of Jun 17, 2026, the average yearly pay for machine learning engineer quantization in Lincoln, CA is $134,444.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $161,800.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What cities near Lincoln, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Lincoln, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer

Machine Learning Engineer

Intel

Folsom, CA • On-site

Full-time

Medical, Retirement, PTO

Posted 2 days ago


Intel rating

8.8

Company rating: 8.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

8th of 139 rated electronics manufacturers


Job description

Job Details:Job Description: Our Mission

At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people-powerful in capability, yet honest about its limits and protective of the data and resources it touches.

To get there, we build agentic AI that combines the best of local and cloud intelligence - private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise-data stays private, spend stays predictable, and energy use stays in check.

We're building intelligence that scales without sacrificing trust, cost, or the planet-because the future of AI should belong to the people it serves

Role Summary

We are seeking a **Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.

What you'll do

Work in a dynamic team to:

  • Build evaluation benchmarks and metrics
  • Build and iterate on agent harness, including context engineering, agent memory, tools, skills.
  • Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment
  • Design RL environments and reward functions - Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.
  • Debug and optimize training runs - Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale
What you'll learn / grow into

Curiosity is required. You will develop:

  • How post-training techniques actually move model performance
  • How to make small models punch above their weight as agent backends
  • How model choices interact with runtime constraints on edge hardware
Qualifications:

Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Required Qualifications
  • BS in CS, EE, Math or related STEM field
  • 5+ years software development background
  • 2+ years of hands-on experience in machine learning engineering, data science or ML research
  • Proficient in Python
  • Proficient in LLM architectures, optimization and model training dynamics.
Preferred Qualifications
  • Masters or PhD degrees are preferred.
  • Hands-on experience implementing and scaling the full **post-training pipeline** for language models including supervised fine tuning and reinforcement learning.
  • Previous experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality
  • Ability to own and drive a research agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.
  • Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.
  • Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.
  • Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.
  • Collaborative work style: Comfort with cross-functional collaboration.
  • Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.
  • Ability to learn new technologies fast and adapt to changes with open-mindedness.

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Benefits at Intel

Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.

Job Type:Shift:Shift 1 (United States of America)Primary Location: US, California, Santa ClaraAdditional Locations:US, Arizona, Phoenix, US, California, Folsom, US, Oregon, HillsboroBusiness group:The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them.Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/ABenefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $170,500.00-315,490.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

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Benefits

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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968